Motion based video super resolution using edge directed interpolation and complex wavelet transform

An image resolution enhancement approach based on discrete wavelet transform (DWT) and new edge-directed interpolation (NEDI) for degraded satellite images by geometric distortion to correct the errors in image geometry and recover the edge details of directional high-frequency subbands is proposed. The observed image is decomposed into four frequency subbands through DWT, and then the three high-frequency subbands and the observed image are processed with NEDI. To better preserve the edges and remove potential noise in the estimated high-frequency subbands, an adaptive threshold is applied to process the estimated wavelet coefficients. Finally, the enhanced image is reconstructed by applying inverse DWT. Four criteria are introduced, aiming to better assess the overall performance of the proposed approach for different types of satellite images. A public satellite images data set is selected for the validation purpose. The visual and quantitative results show the superiority of the proposed approach over the conventional and state-of-the-art image resolution enhancement techniques.

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“…Many DT-CWT-based resolution enhancement methods [33][34][35] attempt to address this problem. In Ref.…”

Section: Proposed Resolution Enhancement Approachmentioning

confidence: 99%

Satellite image resolution enhancement using discrete wavelet transform and new edge-directed interpolation

Witwit

Zhao

Jenkins

et al. 2017

J. Electron. Imaging

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“…This section gives the details explanation about the super resolution technique discussed in [31]. In this method (MBSR) after detecting the motion region, it is …”

Section: Transforms (Mbsr)mentioning

confidence: 99%

“…In this work we applied new edge-directed interpolation (NEDI) [40] which improved the performance of EDI [78] by obtaining a resolution enhanced image which is not smooth perpendicular to edges and is smooth parallel to edges. The stages of the technique demonstrated in [31] are outlined below:…”

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confidence: 99%

Motion block based video super resolution

Izadpanahi

Demirel

2013

Digital Signal Processing

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A multi-frame super resolution process can be used for enhancing the resolution of video frames by employing the information of consecutive low-resolution frames taken from almost the same scene. Most of these super resolution algorithms are only suitable for global motion model. Nevertheless, if a local motion pattern such as movements of some objects happens between the low resolution frames a global motion model cannot provide efficient performance. Considering this problem, we propose a novel super resolution framework, where the moving and static regions in video frames are processed separately. Occlusion is another issue, which is not considered in most of the video super resolution processes. This problem occurs when a new object appears or an object disappears in the video frames. The proposed motionblock based super resolution method not only offers a local motion model but also deals with the occluded areas in a proper way.This thesis presents a new video super resolution technique, based on the motion and static areas of the low resolution video frames. In order to separate the motion and static blocks, a block motion estimation method is employed between a reference and its neighbouring frames. Among the motion blocks, the occluded blocks are identified using an adaptive threshold applied on each block individually. Structure-adaptive normalized convolution (SANC) reconstruction method is used to generate the high resolution static and motion blocks where discrete wavelet transform (DWT) based interpolation is used to produce the high resolution occluded blocks. The static and motion blocks are combined into a high resolution frame.

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“…Numerous algorithms have been proposed in the literatures [1][2][3][4][5][6][7][8][9][10][11][12][13]. They can be broadly classified into three categories, i.e., interpolation-based, learning-based and reconstruction-based methods.…”

Section: Introductionmentioning

confidence: 99%

“…Most of reconstruction-based SR methods proposed in the literature consist of the three stages, i.e., image registration, interpolation and restoration (i.e., inverse procedure), where the last two steps are usually implemented jointly. In [11,12], Izadpanahi et al jointly utilize the super-resolution and edge-directed interpolation to reconstruct high resolution images.…”

Section: Introductionmentioning

confidence: 99%

Video super-resolution with registration-reliability regulation and adaptive total variation

Zhang

Xiong

et al. 2015

Journal of Visual Communication and Image Representation

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Motion based video super resolution using edge directed interpolation and complex wavelet transform

Cited by 19 publications

References 18 publications

Satellite image resolution enhancement using discrete wavelet transform and new edge-directed interpolation

Satellite image resolution enhancement using discrete wavelet transform and new edge-directed interpolation

Motion block based video super resolution

Video super-resolution with registration-reliability regulation and adaptive total variation

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